摘要
动态矩阵控制(DMC)是模型预测控制(modelpredictivecontrol)的一种典型算法,通过模型预测、在线滚动优化和反馈校正来对被控系统实施优化控制,能有效处理系统输入输出约束和抑制随机干扰。为了使具有概率约束的被控对象具有更好的动态响应速度和鲁棒性,在优化性能指标函数中引入跟踪误差的微分项,再通过高斯近似把概率约束指标转换为确定约束,建立有约束DMC预测控制算法。理论分析和计算机仿真结果表明了该算法使系统具有更好的控制品质。
Dynamic matrix control （DMC） is a typical control algorithm of model predictive control. Through model prediction, on-line rolling optimization and feedback rectification, the optimization of controlled system is implemented. The constraints of system input and output can be effectively handled, and random interference can be restrained. In order to get better dynamic response speed and robustness for controlled objects with probabilistic constraint, differential element of tracking error is introduced into optimization objective function, then the probabiliStic constraint is converted into deterministic constraint by using Gaussian approximation, thus constraint DMC predictive control algorithm is established. The results of theoretics analysis and computerized simulation prove that this approach makes the system have better control quality.
出处
《自动化仪表》
CAS
2006年第12期10-12,共3页
Process Automation Instrumentation
基金
南京信息工程大学科研资助项目基金(编号:Qd11)
关键词
动态矩阵控制
概率约束
跟踪误差变化率
优化指标函数
Dynamic matrix control Probabilistic constraints Rate of change for tracking error Optimization objective function
